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Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling

Overview of attention for article published in BMC Genomics, March 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

twitter
10 tweeters

Citations

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19 Dimensions

Readers on

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82 Mendeley
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1 CiteULike
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Title
Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling
Published in
BMC Genomics, March 2015
DOI 10.1186/s12864-015-1404-9
Pubmed ID
Authors

Trevor W Rife, Shuangye Wu, Robert L Bowden, Jesse A Poland

Abstract

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of these objectives. We have developed spiked genotyping-by-sequencing (sGBS), which combines targeted amplicon sequencing with reduced representation genotyping-by-sequencing. To minimize the cost of targeted assays, we utilize a small percent of sequencing capacity available in runs of GBS libraries to "spike" amplified targets of a priori alleles tagged with a different set of unique barcodes. This open platform allows multiple, single-target loci to be assayed while simultaneously generating a whole-genome profile. This dual-genotyping approach allows different sets of samples to be evaluated for single markers or whole genome-profiling. Here, we report the application of sGBS on a winter wheat panel that was screened for converted KASP markers and newly-designed markers targeting known polymorphisms in the leaf rust resistance gene Lr34. The flexibility and low-cost of sGBS will enable a range of applications across genetics research. Specifically in breeding applications, the sGBS approach will allow breeders to obtain a whole-genome profile of important individuals while simultaneously targeting specific genes for a range of selection strategies across the breeding program.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 3 4%
United States 3 4%
Netherlands 1 1%
Italy 1 1%
Brazil 1 1%
Australia 1 1%
Canada 1 1%
United Kingdom 1 1%
Unknown 70 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Researcher 20 24%
Student > Master 10 12%
Other 7 9%
Student > Postgraduate 7 9%
Other 12 15%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 60 73%
Biochemistry, Genetics and Molecular Biology 7 9%
Computer Science 2 2%
Business, Management and Accounting 1 1%
Mathematics 1 1%
Other 1 1%
Unknown 10 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 January 2016.
All research outputs
#3,885,580
of 19,211,930 outputs
Outputs from BMC Genomics
#1,783
of 9,730 outputs
Outputs of similar age
#53,201
of 235,271 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 19,211,930 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,730 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 235,271 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them